| You're right, I'm not a well-known researcher, simply an entrepreneur who started to publish academic papers. However, I do have a long history of diving deep into fields and building practical, open-source solutions to major problems I perceive in the fields. 15 years ago I started with social networks and PHP:
https://github.com/Qbix
http://laweekly.com/restoring-healthy-communities/ 8 years ago I got into smart contracts on EVM, which was the SOTA at the time:
https://github.com/Intercoin
https://intercoin.org/applications About a year and a half ago I started teaching a course on AI at a university not far from NYU where I studied... and that's what got me into this: https://vimeo.com/1063008765/c7ef3abcc5 I try to document everything on GitHub and popular articles, but only recently started publishing academic papers on arXiv and plan to actually start submitting them for real publications. While I build, I realized that I should start publishing any novel theoretical results that underpin my work. I plan to publish actual code in a few weeks. To be fair, TurboQuant is also a purely theoretical paper. I just wanted to get this out and share. |
TurboQuant is not a purely theoretical paper. Section 4 "Experiments" (page 15) [0] has a bunch of figure based on actual GPU computations.
[0]: https://arxiv.org/abs/2504.19874